---
library_name: peft
license: other
base_model: deepseek-ai/deepseek-coder-1.3b-base
tags:
- generated_from_trainer
model-index:
- name: lemexp-task1-v2-template_small-deepseek-coder-1.3b-base-ddp-12lr-v2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# lemexp-task1-v2-template_small-deepseek-coder-1.3b-base-ddp-12lr-v2

This model is a fine-tuned version of [deepseek-ai/deepseek-coder-1.3b-base](https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1541

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0012
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.3986        | 0.2001  | 720   | 0.3279          |
| 0.3106        | 0.4001  | 1440  | 0.2887          |
| 0.2816        | 0.6002  | 2160  | 0.2783          |
| 0.2741        | 0.8002  | 2880  | 0.2706          |
| 0.2644        | 1.0003  | 3600  | 0.2729          |
| 0.2559        | 1.2003  | 4320  | 0.2616          |
| 0.2526        | 1.4004  | 5040  | 0.2572          |
| 0.248         | 1.6004  | 5760  | 0.2575          |
| 0.2467        | 1.8005  | 6480  | 0.2575          |
| 0.2414        | 2.0006  | 7200  | 0.2458          |
| 0.2347        | 2.2006  | 7920  | 0.2465          |
| 0.2335        | 2.4007  | 8640  | 0.2434          |
| 0.2304        | 2.6007  | 9360  | 0.2338          |
| 0.2273        | 2.8008  | 10080 | 0.2284          |
| 0.2272        | 3.0008  | 10800 | 0.2300          |
| 0.2176        | 3.2009  | 11520 | 0.2303          |
| 0.2208        | 3.4009  | 12240 | 0.2261          |
| 0.2142        | 3.6010  | 12960 | 0.2264          |
| 0.2121        | 3.8011  | 13680 | 0.2194          |
| 0.2111        | 4.0011  | 14400 | 0.2199          |
| 0.203         | 4.2012  | 15120 | 0.2156          |
| 0.2029        | 4.4012  | 15840 | 0.2122          |
| 0.1986        | 4.6013  | 16560 | 0.2297          |
| 0.1994        | 4.8013  | 17280 | 0.2142          |
| 0.1958        | 5.0014  | 18000 | 0.2057          |
| 0.1865        | 5.2014  | 18720 | 0.2046          |
| 0.1858        | 5.4015  | 19440 | 0.2081          |
| 0.1862        | 5.6016  | 20160 | 0.2052          |
| 0.1864        | 5.8016  | 20880 | 0.1912          |
| 0.1798        | 6.0017  | 21600 | 0.1945          |
| 0.173         | 6.2017  | 22320 | 0.1919          |
| 0.1732        | 6.4018  | 23040 | 0.1874          |
| 0.1704        | 6.6018  | 23760 | 0.1858          |
| 0.1704        | 6.8019  | 24480 | 0.1879          |
| 0.1669        | 7.0019  | 25200 | 0.1847          |
| 0.1602        | 7.2020  | 25920 | 0.1802          |
| 0.1575        | 7.4021  | 26640 | 0.1825          |
| 0.1568        | 7.6021  | 27360 | 0.1821          |
| 0.154         | 7.8022  | 28080 | 0.1738          |
| 0.1547        | 8.0022  | 28800 | 0.1749          |
| 0.144         | 8.2023  | 29520 | 0.1749          |
| 0.1413        | 8.4023  | 30240 | 0.1703          |
| 0.143         | 8.6024  | 30960 | 0.1714          |
| 0.1396        | 8.8024  | 31680 | 0.1650          |
| 0.1398        | 9.0025  | 32400 | 0.1690          |
| 0.1274        | 9.2026  | 33120 | 0.1676          |
| 0.1261        | 9.4026  | 33840 | 0.1638          |
| 0.1274        | 9.6027  | 34560 | 0.1662          |
| 0.1263        | 9.8027  | 35280 | 0.1579          |
| 0.1224        | 10.0028 | 36000 | 0.1585          |
| 0.1123        | 10.2028 | 36720 | 0.1597          |
| 0.1114        | 10.4029 | 37440 | 0.1561          |
| 0.1102        | 10.6029 | 38160 | 0.1574          |
| 0.1095        | 10.8030 | 38880 | 0.1542          |
| 0.1101        | 11.0031 | 39600 | 0.1520          |
| 0.0992        | 11.2031 | 40320 | 0.1565          |
| 0.0972        | 11.4032 | 41040 | 0.1554          |
| 0.0957        | 11.6032 | 41760 | 0.1548          |
| 0.0955        | 11.8033 | 42480 | 0.1541          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0